Forestry information management systems and methods streamlined by automatic biometric data prioritization

ABSTRACT

Methods and systems are presented for obtaining photographic data recently taken via one or more airborne vehicles (drones, e.g.) and for prioritizing forestry-related review and decision-making as an automatic response to the content of the photographic data even where remote decision-makers are only available via limited-bandwidth connections.

RELATED APPLICATION

This application claims priority to U.S. Provisional App. No. 62/240,167(“Aerial Tree Planting System and Method of Use”) filed 12 Oct. 2015 andincorporates the same herein by reference in its entirety.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary special-purpose-hardware schematicdepicting an aircraft.

FIG. 2 illustrates an exemplary special-purpose-hardware schematicdepicting an aircraft.

FIG. 3 illustrates an exemplary special-purpose system by which astation thereof interacts with a network.

FIG. 4 illustrates an exemplary special-purpose system by which variousportable client devices interact with a network.

FIG. 5 illustrates a server in which one or more technologies may beimplemented.

FIG. 6 illustrates a client device in which one or more technologies maybe implemented.

FIG. 7 illustrates a flow chart of an information management routine inaccordance with at least one embodiment.

FIG. 8 illustrates a data flow diagram relating to one or moreinformation management routines described herein.

FIG. 9 illustrates various forestry-related verdicts.

FIG. 10 illustrates various forestry-related depictions.

FIG. 11 illustrates a schematic of a physical system relating to one ormore information management routines described herein.

FIG. 12 illustrates another flow chart of an information managementroutine in accordance with at least one embodiment.

FIG. 13 illustrates additional aspects of various forestry-relateddepictions.

FIG. 14 illustrates a scatter plot depicting scalar biometric datasetsderived from raw data taken at several different times and atime-dependent scalar biometric range to which each such datasetpertains.

DETAILED DESCRIPTION

The detailed description that follows is represented largely in terms ofprocesses and symbolic representations of operations by conventionalcomputer components, including a processor, memory storage devices forthe processor, connected display devices and input devices. Furthermore,some of these processes and operations may utilize conventional computercomponents in a heterogeneous distributed computing environment,including remote file servers, computer servers and memory storagedevices.

The phrases “in one embodiment,” “in various embodiments,” “in someembodiments,” and the like are used repeatedly. Such phrases do notnecessarily refer to the same embodiment. The terms “comprising,”“having,” and “including” are synonymous, unless the context dictatesotherwise.

“Above,” “artificial,” “at least,” “automatic,” “below,” “biometric,”“by,” “concerning,” “conditional,” “current,” “first,” “forestry,” “inresponse,” “indicated,” “local,” “location-specific,” “obtained,” “of,”“optical,” “outside,” “part,” “photographic,” “prioritized,” “received,”“remote,” “said,” “scalar,” “second,” “selected,” “some,” “thereof,”“third,” “transmitted,” “unmanned,” “wherein,” “within,” or other suchdescriptors herein are used in their normal yes-or-no sense, not asterms of degree, unless context dictates otherwise. In light of thepresent disclosure those skilled in the art will understand from contextwhat is meant by “remote” and by other such positional descriptors usedherein. Terms like “processor,” “center,” “unit,” “computer,” or othersuch descriptors herein are used in their normal sense, in reference toan inanimate structure. Such terms do not include any people,irrespective of their location or employment or other association withthe thing described, unless context dictates otherwise. “For” is notused to articulate a mere intended purpose in phrases like “circuitryfor” or “instruction for,” moreover, but is used normally, indescriptively identifying special purpose software or structures.

Reference is now made in detail to the description of the embodiments asillustrated in the drawings. While embodiments are described inconnection with the drawings and related descriptions, there is nointent to limit the scope to the embodiments disclosed herein. On thecontrary, the intent is to cover all alternatives, modifications andequivalents. In alternate embodiments, additional devices, orcombinations of illustrated devices, may be added to, or combined,without limiting the scope to the embodiments disclosed herein.

Referring now to FIG. 1, there is shown a system 100 that includes anaircraft 130 usable with the present invention. For the sake of brevity,conventional components related to graphics and image processing,navigation, flight planning, unmanned vehicle controls, and otherfunctional aspects of the unmanned airborne vehicle (UAV) relating toflying may not be described in detail herein.

As shown, system 100 may (optionally) include one or more instances ofinterchangeable batteries/UAV fuel 126; of a central processing unit(CPU) programmed with routes and a link to firing 128; of a firingcontrol mechanism 161; of an interchangeable compressed gas canister162; of gas regulator configurations 163; of global positioning (GPS)systems and integrated navigation sensor (INSS) systems 171; of opticalimaging sensors 172 (multispectral, hyperspectral, or RGB sensors,e.g.); of LIDAR/LADAR sensors 173; of memory storage 174; of satellite(SAT) uplinks 175. Moreover, the aircraft (UAV, e.g.) may furthercomprise additional sensor payloads such as thermal image sensors.

The LIDAR/LADAR sensor 173 may (optionally) be configured to measurereflective values of materials, such as soil, on the ground. Themeasured reflective values are transmitted to the CPU, which determineswhether the reflective values fall within a predetermined thresholdrange. If the reflective values fall within the predetermined threshold,the area is designated as a qualified planting area for trees. If thereflective values fall outside of the predetermined range, the area isdisqualified as a planting area. It is contemplated, however, that thepresent system may be used for planting and monitoring the growth offother types of plants, crops, and the like.

Similarly, the hyperspectral image sensor may be used to gain detailedinformation about the ground. More specifically, the hyperspectral imagesensor allows an operator or another end user to “see” the soil, water,and nutrient levels on the ground, particularly in areas that aredifficult to access manually. If a spectral signature for an areaidentifies materials suitable for planting trees, the area is identifiedas a qualified planting area.

It is contemplated that the CPU is configured to collect and consolidatemultiple data sets of data from various sensors as a key attribute toplotting microsites. In this way, the consolidated data is used togenerate a single map for a subsequent planting phase. Additionally, ifthe data obtained from the LIDAR/LADAR sensor and the hyperspectralsensor or another sensor is inconsistent, then the sensors areconfigured to re-scan the area until there are no more discrepancies. Assuch, operators can conduct reconnaissance of a terrain remotely in aconvenient and efficient manner.

Measured data and the grid coordinates of the area associated therewithmay be stored in the memory unit or transmitted to a remote server viathe SAT uplink. Preferably, the grid coordinates are determined via theGPS, INS, or other suitable navigation systems. Additionally, a GPScorrection method such as real-time kinematic (RTK) is used to increasethe accuracy of the positioning. The areas designated as a qualifiedplanting area may be saved as a part of a planned route for thesubsequent planting phase. Within each of the planting areas, aplurality of microsites is identified.

Microsites are points where material delivery operations can occur(where seeds can be planted or herbicides applied, e.g.). Targetedpoints are selected based on several factors, such as the desired numberof plantings per acre, species of trees, surface tension of the soil,soil type, and beneficial landscape features. The microsites areseparated at regular intervals, depending upon spacing specified by anexpert. In one embodiment, each planting microsite is seven feet apartso as to provide enough room for plant growth.

The aircraft is further equipped with a pneumatic firing apparatus,which comprises a firing control mechanism, a pneumatic system, aplurality of gas regulators, connecting hoses and chambers, and a seedbarrel, in which the seed barrel 190 comprises interchangeable seedmagazines 188 therein. The foregoing components, including the sensors,memory unit, and the processor as described above, are powered viainterchangeable batteries or fuel, depending upon embodiment.Additionally, all of the components on the aircraft are light in weightin order to increase fuel efficiency or to preserve power.

The one or more seed magazines 188 comprise individual seed capsules.The seed capsules comprise a housing that is composed of polyvinylalcohol or other suitable non-toxic and dissolvable material, in whichthe housing has a defined interior volume for storing seeds therein. Theseed capsules also comprise hydrogels, polymers, or polyacrylamides forpreventing the seeds from drying out. Having hydrogels, polymers, orpolyacrylamides in the seed capsules and near the roots improves accessto water while maintaining aeration. Additionally, the seed capsulesfurther comprise fertilizers, mycorhizal fungi, mycelium, pesticides,herbicides, predator deterrents, or any combination thereof.

As the aircraft flies over the microsites, the pneumatic system isadapted to eject the seed capsules. It is contemplated that themicrosites are targeted so that the seed capsules are shot toward themicrosites and landed therein. Additionally, the gas regulators optimizethe pressure to control the velocity of the seed capsule as it is shot.The velocity may vary depending on various factors such as wind speed,soil surface tension, and the like. In some embodiments, the gasregulators may be adjusted manually or programmed to adjustautomatically for different planting areas. Because the seed capsulesare dissolvable, the seeds need not be buried or penetrated in soil andallows the root structure of the seed plant to expand without hindrance.

In some variants, the present invention may (optionally) furthercomprise seed amendment pellets. The pellets comprise a shotgun shellshape and include mycorhizzal fungi inoculated medium, pesticides,herbicides, fertilizers, odors or compounds, hydrogels, beneficialplants, multiple seeds, or any combination thereof.

Referring now to FIG. 2, there is shown a system in which one or moretechnologies may be implemented. A station 235 (a truck or building,e.g.) is operably linked to a remote network 268 through a satelliteuplink or similar signal path as shown. The station is in or near a landtract 250A of interest, with current photographs having been taken viaone or more cameras (aboard one or more instances of vessel 230 thatwas/were then airborne, e.g.) depicting several respective positions255A-C near the position 255D of station 235. Each vessel 230 mayinclude one or more motor driven propellers 239 (each being an airplane231 or helicopter 232 or unmanned aerial vehicle 233, e.g.).Alternatively or additionally, such photographs (or location-specificphotographic data portion, e.g.) may each be associated with one or moreinstances of coordinates 253; timestamps 254; times 291, 292, 293 in anevent sequence designation (timeline 295, e.g.); biometrics 270(detected in or computed from a photograph, e.g.) or limits 261, 262,263 pertaining to a given biometric. For example, a subject matterexpert may define one or more ranges 277A-B between pairs of such limits261-263 as shown.

Referring now to FIG. 3, there is shown an exemplary operationalschematic 300 that may reflect one or more technologies of the presentsystem. It is contemplated that multiple instances of UAV 233 canoperate concurrently, for example, during two primary phases.Additionally, in some contexts one operator from the ground can controlmultiple UAVs at one time. In one embodiment, one operator can controlapproximately ten to fifteen UAVs at one time. In another embodiment,the operator may operate different groups of UAVs at different times. Inyet another embodiment, the UAVs may be programmed to operateindependently so that an operator is not needed.

During a “reconnaissance” phase 360, UAV 233 flies over an area. Whileairborne, the sensors of the UAV help identify suitable planting areasand microsites within the planting areas by collecting data. Thecollected data is processed via the CPU and stored in the memory unit ortransmitted to a remote database server. Based on the data, at phase370, the CPU maps at least one route for planting. Alternatively, thecollected data is transmitted to another server or a mapping module onground that may be configured to perform route mapping.

During a “planting” phase 380, UAV 233 flies over a preplanned route andlaunches the seed capsules when it is within a shooting range of themicrosites. In this way, the UAV can fire encapsulated tree seeds intothe ground in places identified as good growing area. Optionally, theUAV may be programmed to fly over the planned route periodically tomonitor seed growth.

FIG. 4 illustrates an exemplary network topology of an informationmanagement system 400 in accordance with various embodiments. A centralinformation management server 500 (see FIG. 5) is in data communicationwith a plurality of client devices 600A-C (see FIG. 6) via one or morenetworks 468. In various embodiments, network 468 may include theInternet, one or more local area networks (“LANs”), one or more widearea networks (“WANs”), cellular data networks, and/or other datanetworks. Network 468 may, at various points, be a wired and/or wirelessnetwork. Remote information management server 500 may be in datacommunication with one or more information management data stores 465.

In various embodiments, any of client devices 600A-C may be networkedcomputing devices having form factors including general purposecomputers (including “desktop,” “laptop,” “notebook,” “tablet”computers, or the like); mobile phones; watches, glasses, or otherwearable computing devices. In the example shown in FIG. 4, clientdevice 600A is depicted as a laptop/notebook computer, client device600B is depicted as a handheld device, and client device 600C isdepicted as a computer workstation. In various embodiments there may befewer or many more respondent devices than are shown in FIG. 4.

As is described in more detail below, in various embodiments, remoteinformation management server 500 may be a networked computing devicegenerally capable of accepting requests over network 468 e.g. from anyone of respondent devices 600A-C and/or other networked computingdevices (not shown), and providing responses accordingly. In a typicalcontext, one or more devices 600A-B networked together as describedherein may rely upon a bandwidth-limited signal path 401A-B and one ormore other devices 600C also networked will rely upon abandwidth-unlimited signal path 401C, the significance of which will beappreciated by one skilled in the art in light of the disclosure thatfollows. In general, bandwidth-limited signal path 401A-B and thedevices 600A-B that rely upon them are not adequate to allow a humanuser thereof to review pictographic and other bandwidth-intensive dataand provide a timely verdict thereon (a diagnosis, work request, orother consequential decision soon enough to make a difference, e.g.).

The functional components of an exemplary information management server500 that remotely supports advanced interactions with various clientdevices 600A-C are described below in reference to FIG. 5.

FIG. 5 illustrates a server 500 in which one or more technologies may beimplemented. In respective embodiments, server 500 may be ageneral-purpose computer or may include special-purpose components notshown. As shown in FIG. 5, exemplary server 500 includes one or moreprocessing units 502 in data communication with one or more memories 504via one or more buses 516. Each such memory 504 generally comprises someor all of random access memory (RAM), read-only memory (ROM), and/or apermanent mass storage device, such as a disk drive, flash memory, orthe like. Client device 500 may also include one or more instances ofnetwork interfaces 506, of user inputs 508, of displays 512, or ofspeakers (not shown).

As shown, memory 504 of exemplary server 500 may store an operatingsystem 510, as well as program code for a number of softwareapplications, such as a client hosting application 514. These and othersoftware components, as well as various data files (not shown) may beloaded into memory 504 via network interface (optional) 506 (or via aselectively removable computer readable storage medium 518, such as amemory card or the like). For hardware functions such as networkcommunications via network interface 506, obtaining data via user input508, rendering data via display 512 and/or speaker, and alposition ofmemory 504 to various resources, operating system 510 may act as anintermediary between software executing on server 500 and the server'shardware.

For example, operating system 510 may cause a representation of locallyavailable software applications, such as client hosting application 514,to be rendered locally (via display 512, e.g.). If operating system 510obtains, e.g. via user input 508, a selection of client hostingapplication 514, operating system 510 may instantiate a client hostingapplication 514 process (not shown), i.e. cause processing unit 502 tobegin executing the executable instructions of client hostingapplication 514 and allocate a portion of memory 504 for its use. Insome variants, moreover, a download service 524 resident in memory mayallow apps (inventoried in medium 518, e.g.) to be downloaded uponrequest to authorized client devices as described below. Alternativelyor additionally, operations described below may be implemented withspecial-purpose circuitry 522 resident in server 500 as described below.

Although an exemplary server 500 has been described, a server 500 may beany of a great number of computing devices capable executing programcode, such as the program code corresponding to hosting application 514.Alternatively or additionally, the structures described with referenceto FIG. 5 may likewise be implemented by a special-purpose peer computerin a peer-to-peer network.

FIG. 6 illustrates a client device 600 in which one or more technologiesmay be implemented. In respective embodiments, client device 600 may bea general-purpose computer or may include special-purpose components notshown. As shown in FIG. 6, exemplary client device 600 includes one ormore processing units 602 in data communication with one or morememories 604 via one or more buses 616. Each such memory 604 generallycomprises some or all of random access memory (RAM), read-only memory(ROM), and/or a permanent mass storage device, such as a disk drive,flash memory, or the like. Client device 600 may also include one ormore instances of network interfaces 606, of user inputs 608, ofdisplays 612, or of speakers (not shown).

As shown, memory 604 of exemplary client device 600 may store anoperating system 610, as well as program code for a number of softwareapplications, such as a client web browser application 614. Client webbrowser application 614 is a software application by which, under servercontrol, client devices can present data to users and transmit dataentered by them. These and other software components, as well as variousdata files (not shown) may be loaded into memory 604 via networkinterface (optional) 606 (or via a selectively removable computerreadable storage medium 618, such as a memory card or the like). Forhardware functions such as network communications via network interface606, obtaining data via user input 608, rendering data via display 612and/or speaker, and alposition of memory 604 to various resources,operating system 610 may act as an intermediary between softwareexecuting on client device 600 and the client device's hardware.

For example, operating system 610 may cause a representation of locallyavailable software applications, such as client web browser application614, to be rendered locally (via display 612, e.g.). If operating system610 obtains, e.g. via user input 608, a selection of client web browserapplication 614, operating system 610 may instantiate a client webbrowser application 614 process (not shown), i.e. cause processing unit602 to begin executing the executable instructions of client web browserapplication 614 and allocate a portion of memory 604 for its use.Alternatively or additionally, operations described below may beimplemented with special-purpose circuitry 622 resident in client device600 as described below.

FIG. 7 illustrates an information management routine 700 suitable foruse with at least one embodiment. As will be recognized by those havingordinary skill in the art, not all events of information management areillustrated in FIG. 7. Rather, for clarity, only those steps reasonablyrelevant to describing the forestry information management aspects ofroutine 700 are shown and described. Those having ordinary skill in theart will also recognize the present embodiment is merely one exemplaryembodiment and that variations on the present embodiment may be madewithout departing from the scope of the broader inventive concept as itis defined by the claims below.

Execution block 705 depicts information management routine 700 obtainingcurrent photographic data of a land tract, in which “current” means thatat least some of the data was detected from first, second, and thirdpositions of the land tract via one or more sensors aboard one or moreairborne vehicles as optical energy less than 3 days ago (at time T1).This can occur, for example, in a context in which the “positions” arerespective positions 255A-C depicted in FIG. 2.

Execution block 710 depicts information management routine 700 derivinga depiction (at time T2) of the land tract from the photographic data,in which a first location-specific artificial biometric of the depictionis associated with the first position of the land tract, in which asecond location-specific artificial biometric of the depiction isassociated with the second position of the land tract, and in which athird location-specific artificial biometric of the depiction isassociated with the third position of the land tract. In some variants,execution block 710 may include selectively including a photograph of atleast a part of the land tract that overlaps the third position (whileomitting from the derived depiction at least some photographic datadepicting the first or second positions of the land tract).

As used herein, an “artificial biometric” may refer to a human- ormachine-made estimate (measurement or other quantification, e.g.) of oneor more physical traits derived to characterize a health-related statusof one or more non-animal life forms at a known position. It maydescribe one or more health-indicative physical traits of fungi orlichen, for example, or to adverse effects (by fire, flood, animalgrazing, or infestation, e.g.) upon one or more crops. It may describecolorimetric or other filtered attributes tailored to identify anddistinguish a life form of interest from some other having similarattributes (scotch broom versus bracken fern, e.g.). But mere rawoptical data (unmodified reflectance or brightness measurements, e.g.)or image data that has merely undergone conventional content-neutraldata processing (quantization, encoding, compression, shading, e.g.) isnot an “artificial biometric” as used herein. Though many artificialbiometrics can be derived from pixel hue in light of teachings herein,for example, those skilled in the art will recognize that mere raw pixelhue and pixel grouping shape are not “artificial biometrics” as usedherein.

Distance-indicative artificial biometrics that are derived (at leastpartly) from optical data and of interest herein include standdimensions, tree heights, trunk diameters, nearest-crop-tree spacings,and other such distances as well as computations based thereon(averages, multiplicative products, comparisons, or other suchcomputations partly based on elevation, grade, rainfall, or otherposition-dependent or historical determinants, e.g.).

Execution block 720 depicts information management routine 700determining that a scalar value of the first location-specificartificial biometric of the depiction is below a selected range. Thiscan occur, for example, in a context in which the range 277A is“selected” by a user of a client device 600A who only plans to beavailable for diagnoses and decisionmaking via a limited-bandwidthsignal path 401A during forestry operations described herein.

Execution block 730 depicts information management routine 700determining that a scalar value of the second location-specificartificial biometric of the depiction is above the selected range.

Execution block 740 depicts information management routine 700determining that a scalar value of the third location-specificartificial biometric of the depiction is within the selected range.

Execution block 775 depicts information management routine 700generating an automatic prioritization of the third position of the landtract over the first and second positions of the land tract partly basedon the scalar value of the third location-specific artificial biometricof the depiction being within the selected range, partly based on thescalar value of the first location-specific artificial biometric of thedepiction being below the selected range, and partly based on the scalarvalue of the second location-specific artificial biometric of thedepiction being above the selected range.

Execution block 785 depicts information management routine 700manifesting the automatic prioritization of the third position of theland tract over the first and second positions of the land tract byexpressing the prioritization to a remote party.

Execution block 790 depicts information management routine 700 receivinga verdict (at time T3) at least about the third position from the remoteparty within two days after that party received the automaticprioritization of the third position. This can occur, for example, in acontext in which the times T1-T3 are respective event times 291-293depicted in FIG. 2 and in which a timely verdict could not otherwise beachieved without allowing some other party (onsite at land tract 250A,e.g.) to provide the verdict.

The information management routine 700 ends at termination block 799.

FIG. 8 illustrates a dataflow schematic suitable for use with at leastone embodiment. Operational parameters 805A including a biometric range“A” are transmitted from client device 600A to station 235 at which aplurality of drones 832 (instances of aircraft 130, e.g.) are based andoperated. Operational parameters 805B including a biometric range “B”are likewise transmitted from client device 600B to station 235. One ormore of the drones 832 are accordingly dispatched take airborne data 815using the received operating parameters 805A-B. In some variants suchairborne data 815 may be via one or both of hyperspectral imaging orLIDAR or LADAR (using one or more sensors 172, 173 described above,e.g.) and with the one or more removable/interchangeable compressed gascanisters 162 and seed magazines 188 of that drone 832 left behind toextend that drone's range. Some or all of the current airborne data 815is then transmitted 820 as raw data 820 to server 500. Server 500 thenapplies one or both of ranges “A” and “B” to the raw data 820 todetermine (by executing block 775, e.g.), where appropriate, anautomatic prioritization of the third position 255C of the land tract250A over the other positions 255A-B of the land tract. This canmanifest itself, for example, as a ranking that prioritizes an image ofposition 255C and causes that image to be transmitted automatically to aclient device 600A (in use by and associated with party 898A as shown,e.g.) as an automatic and conditional response to that client device600A having provided the range “A” within which the thirdlocation-specific artificial biometric fell. In some contexts, thedepiction containing that image may be large enough (several megabytesor larger, e.g.) so that it only arrives at device 600A overnight(within 16 hours of having been taken, e.g.) by virtue of having beenselected (as part of prioritized data selection 865A, e.g.) and sentautomatically. This can occur, for example, in a context in which landtract 250A is remote from high-bandwidth connections and in whichprioritized data selection 865A omits shape-indicative data pertainingto lower-priority positions 255A-255B for which the location-specificartificial biometrics were out-of-range.

Alternatively or additionally, in some contexts the generating adepiction 825 include a determination (either by server 500 or by aprocessing unit 602 within vessel 230, e.g.) that an artificialbiometric pertaining to a different position 255A may be prioritized asto a different client device 600B (in use by and associated with party898B as shown, e.g.) by virtue of having fallen within a range 277Bprovided by that client device 600B. This can occur, for example, in acontext in which a corresponding biometric pertaining to position 255Bis below range 277B; in which a corresponding biometric pertaining toposition 255C is above range 277B; in which the conditional prioritizeddata selection 865B automatically transmitted to client device 600B islarger than 100 megabytes (including at least an image of position 255A,e.g.) but smaller than 100 terabytes (not including all the currentimages of land tract 250A in the current raw dataset, e.g.); in whichsuch transmission preceded a long delay 870 (of 24-48 hours, e.g.) onlyby virtue of having been automatically prioritized and sent; and inwhich one or more verdicts 875A, 875B (decisions whether to plant ornot, e.g.) would otherwise not have been acted upon 880 until asubsequent deployment (when station 235 returned to land tract 250A morethan a year later, e.g.).

FIG. 9 provides a schematic illustration of various forestry-relatedverdicts 875 as further described herein, residing in a memory 904(optionally implemented in one or more of the above-described memories504, 604 or in a drone 832 or other aircraft 130, e.g.). A “verdict” asused herein may refer to any forestry-related determination (adiagnosis, plan of action, quantified estimate, or other judgment) fromone or more human authorities (experts or device operators, e.g.)pertaining to consequential deployment actions upon land or vegetationat least partly based on current aerial data. As used herein, “current”data refers to measurements or other values that are affected orotherwise updated by a sensor detection (resulting from optical energy,e.g.) that has occurred in a vicinity under study (at or above alocation of interest, e.g.) within six months of such verdict. When nosuch recent data that pertains to an area is used to ascertain a morerecent condition of the vicinity, the older data pertaining to thatvicinity is “not current.”

Such verdicts 875 may each include one or more instances of positivedecisions 901, of negative decisions 902 (not to take an action underconsideration, e.g.), of diagnoses (specifying a noxious organism withan organic species identification 903, e.g.), or of additional workrequests (analyses and verdicts by other human authorities, e.g.). Insome contexts, for example, such positive decisions 901 underconsideration may be expressed as one or more portable moduleidentifiers 921 (a serial number effectively determining which bioactivematerials to apply to the “third position” under consideration.Alternatively or additionally, a verdict 875 may include one or moretask or instruction sequences 922 or defined routes 923 (specifying whenand how a drone-implemented delivery flight will be executed, e.g.).Alternatively or additionally, a verdict 875 may include one or moreinstances of bioactive material identifiers 935 (such as herbicideidentifiers 931, pesticide identifiers 932, fertilizer identifiers 933,or other such deliverable cargo, e.g.). Alternatively or additionally, averdict 875 may express one or more instances of crop speciesidentifications 943 or other components of (positive) planting decisions945.

FIG. 10 provides a schematic illustration of a forestry-relateddepiction 1025 as further described herein, residing in a memory 1004(implemented in one or more of the above-described memories 504, 604 orin a drone 832 or other aircraft 130, e.g.). A “depiction” of a landtract as used herein means a dataset that includes one or morephotographic, categorical, or other descriptive data componentsconcerning respective parts of the land tract. It may include, in someinstances, sets of coordinates 1033 correlated to one or more instancesof photographic or schematic images 1031 of physical features of theland as well as scalar determinants 1032A-C with which the images 1031or coordinates 1033 are correlated. In some variants, for example, sucha depiction may include map data (showing historical water features,e.g.) or other such non-biometric determinants 1032A (that may describesoil composition, localized meteorological data, ground elevation, orthermal or precipitation history, e.g.), or other such measurements thatmay affect but do not directly describe any current occurrence ofnon-motile organisms living upon tracked positions of the land.

FIG. 11 illustrates an information management system 1100 configured tointeract with one or more other tracts 250B-C to which one or moreaircraft 130 as described herein may be deployed. In a first deployment,one or more sensors 1140 aboard aircraft 130 receive and detect energy1108 from several positions 255E-G of tract 250B which is manifests asraw digital data 820 (described with reference to FIG. 8, e.g.) inmemory 1104. Also a portion of raw data 820 is distilled into adepiction 1025A that includes a current location-specific artificialbiometric 1102A-E for each of the positions 255 as shown. The depiction1025A may also include some of the photographic data 1389 initiallycaptured by the one or more sensors 1140. In some variants a CPU 118aboard aircraft 130 may be configured to streamline its operations byredacting portions of the photographic data (see FIG. 13) that areunduly duplicative (depicting some or all images of positions 255J forwhich a significant biometric is not of great interest by virtue ofbeing well understood, e.g.). This can occur, for example, in a contextin which a marginal range 277A is selected (via a botanical consultantusing one or more client devices 600A-B remote from tract 250B, e.g.) sothat a lower limit 261 is below 0.2 and so that an upper limit 252 is0.4; in which a first location-specific artificial biometric 1102A(currently describing position 255H, e.g.) is below the marginal range277A; in which a second location-specific artificial biometric 1102B(currently describing position 255I, e.g.) is above the marginal range277A; in which a third location-specific artificial biometric 1102D(currently describing position 255K, e.g.) is within the marginal range277A; in which the botanical consultant receives a prioritization 1151as a real-time response to a large patch of vegetation exhibiting abiometric 1102D within the marginal range 277A having been detected (atserver 500A, e.g.); in which the consultant has set a limit (a number ofsquare meters as one of the on-board parameters 1145, e.g.) as to whatconstitutes a “large patch”; in which no real-time response wouldotherwise have been sent to the consultant; in which some signal paths401A-D is effectively bandwidth-limited but other signal paths 401E ofinterest are not; and in which the consultant would not otherwise havebeen able to provide a verdict 875C in time to avoid a wastedopportunity (to include position 255K and the rest of the patch in oneor more drones 1131 applying an herbicide to a large adjacent part oftract 250B that includes position 255H, e.g.).

In some contexts current data depicting a first microsite (position255K, e.g.) may be used to characterize an entire “third” position evenwhen that position has been extended to include a succession ofadditional adjacent microsites partly based on the value of thebiometric of each microsite in the succession being within the range 277and partly based on each microsite of the succession being adjacentanother microsite of the succession. The effects of such algorithmicextensions are evident, for example, in the irregular shapes ofpositions 255E-G.

In a later deployment, one or more sensors 1140 (described withreference to FIG. 1, e.g.) aboard aircraft 130 receive and detect energy1108 from several irregularly-shaped positions 255E-G of tract 250Cwhich is then recorded as raw digital data 820 in memory 1104. This canoccur, for example, in a context in which a depiction 1025B reflectingthis data is downloaded via signal path 401D while station 1135 is in avicinity 1196 of tract 250C; in which depiction 1025B manifests abiometric map (having biometric values manifested as alikelihood-indicative or other percentage as shown, e.g.) or programmednavigation routes for one or more drones 1131, e.g.); and in which suchinformation flow 1101 (via server 500A and signal paths 401D-E, e.g.)includes a prioritization 1151 and verdict 875C as described below. Thiscan occur, for example, in a context in which the range has a lowerlimit of 20-25 and an upper limit of 50-70; and in which the “third”position is position 255G.

FIG. 12 illustrates an information management routine 1200 suitable foruse with at least one embodiment. As will be recognized by those havingordinary skill in the art, not all events of information management areillustrated in FIG. 12. Rather, for clarity, only those steps reasonablyrelevant to describing the forestry information management aspects ofroutine 1200 are shown and described. Those having ordinary skill in theart will also recognize the present embodiment is merely one exemplaryembodiment and that variations on the present embodiment may be madewithout departing from the scope of the broader inventive concept as itis defined by the claims below.

Execution block 1215 depicts configuring one or more sensors aboard oneor more aircraft to obtain photographic data in memory thereof bydetecting at least some optical energy at a first time T1 from a landtract (one or more client devices 600A-B remotely configuring one ormore sensors 1140 aboard one or more drones 1131 or airborne vehicles toobtain photographic data in memory thereof by detecting optical energy1108 at a “first” time 291 from land tract 250C, e.g.). This can occur,for example, in a context in which the one or more client devices 600A-Bare “remote” by virtue of being more than 100 kilometers from land tract250C. Alternatively or additionally, the memory may contain map data(indicating historical waterway positions or other indications ofpotential hazards, e.g.) or other background information that may affectcurrent depiction 1025B. In some variants, moreover, execution block1215 may be performed by server 500A or concurrently performed by aparty (a device user operating device 600B, e.g.).

Execution block 1285 depicts obtaining a current depiction of a landtract that includes photographic data from one or more airbornevehicles, wherein a first location-specific artificial biometric of thecurrent depiction is associated with a first position of the land tract,wherein a second location-specific artificial biometric of the currentdepiction is associated with a second position of the land tract, andwherein a third location-specific artificial biometric of the currentdepiction is associated with a third position of the land tract (a drone1131, station 1135, or other client device 600 generating or receivingone or more biometric maps or similar depictions 1025 that includephotographic data depicting a tract 250 as described herein, e.g.). Inmany contexts, such depictions are in fact obtained by a succession ofdevices that pass them along.

Execution block 1295 depicts receiving a verdict concerning said thirdposition of said land tract from a party who has received aprioritization of said third location-specific artificial biometric ofthe current depiction over said first and second location-specificartificial biometrics of the current depiction partly based on a scalarvalue of said third location-specific artificial biometric of thecurrent depiction being within a selected range, partly based on ascalar value of said first location-specific artificial biometric of thecurrent depiction being below said selected range, and partly based on ascalar value of said second location-specific artificial biometric ofthe current depiction being above said selected range (a drone 1131,station 1135, or other client device 600 receiving a verdict 875concerning said third position 255 from a party who has received such aprioritization 1151, e.g.). In many contexts, such verdicts 875 are infact obtained by a succession of devices that pass them along.

The information management routine 1200 ends at termination block 1299.

FIG. 13 illustrates another forestry-related depiction 1025C, residingin a memory 1304 (implemented in one or more of the above-describedmemories 904, e.g.). As an alternative to or in addition to theabove-described datasets, depiction 1025C may include one or moreinstances of prioritizations 1151 (including one or more instances ofconditional notifications 1351 or of rankings 1352, e.g.) or of currentdatasets 1377 (each including one or more instances of current estimates1383 or of current scalar values 1384 as further described below, e.g.),or of photographic data 1389 (including one or more photographs 1387obtained by one or more optical imaging sensors 172 or LIDAR/LADARsensors 173 receiving energy 1108, e.g.) in conjunction with one or moreinstances of timestamps 254 or coordinates from sensor 171. Suchestimates 1383 may include, for each of the positions of interest, oneor more of a distance estimate, a rate estimate, a concentrationestimate, an occurrence estimate, a health-difference index, or acombination of the above (as a biometric or otherwise, depending on whatit measures).

As used herein, a “prioritization” may refer to a conditional automaticnotification (requesting an expedited verdict selectively in response tosome datasets 1377B-C but not to other datasets 1377A, e.g.), a ranking(listing the prioritized item before one or more other items, e.g.), orsome other expression signifying elevated importance relative to that ofa nearby position (microsite, e.g.) or its attributes. In some contexts,respective “prioritizations” may be different for different parties,such as in a context in which client device 600A prioritizes record1068A over one or more other depicted records in response to “66”falling within range “A” (as shown in FIG. 8) and in which client device600B prioritizes record 1068B over one or more other depicted records inresponse to “0.5” falling within range “B.” This can make a significantdifference, for example, in a context in which such ranking triggers aselective automatic download of prioritized records; in which afull-resolution image 1031 is adequate to ensure a correct outcome inone or more of the verdicts 875 at issue and in which a lower-resolutionimage 1031 is not; in which full-resolution images 1031 for thethousands of records 1067 of a given land tract not feasible via alimited bandwidth connection to one or both of the client devices 600via which the respective prioritizations 1151 are downloaded; and inwhich the correct and timely outcomes of at least some verdicts 876 atissue would not otherwise be feasible without a substantial hardwareupgrade (to improve bandwidth of linkages 401A-B, e.g.).

FIG. 14 illustrates a scatter plot depicting a range 277 having upperand lower limits that both increase as a function of one or moredeterminants (time, e.g.) with a succession of current datasets 1377A-Ceach separated by several years. In light of teachings herein, oneskilled in the art will be able to identify various health-indicative orgrowth-indicative artificial biometrics for which such a time-dependentrange 277 would be appropriate. A botanist or other expert who is oncall for making time-critical verdicts 875 in marginal cases, forexample, may in some contexts prefer to select such a range 277 (tominimize false positive and negative priority determinations over time,e.g.) to be calculated. At a first (nominal) time 291A (within a week ofthe average timestamped date, e.g.) a dataset 1377A includes severallocation-specific artificial biometrics of the then-current depiction1025 that are within a selected range 277 as well as severallocation-specific artificial biometrics of the then-current depiction1025 that are above the selected range 277. It will be noted that nolocation-specific artificial biometrics of the then-current depiction1025 are below the selected range 277.

In each of datasets 1377B-C, several location-specific artificialbiometrics of the then-current depiction 1025 are above the selectedrange 277. In dataset 1377B, at least one location-specific artificialbiometrics of the then-current depiction 1025 is within the selectedrange 277, suggesting that said biometric (and the “third” position towhich it pertains) deserves a higher priority 1151 than one or more ofthe other (over-limit or under-limit) biometrics in the dataset 1377B(nominally) corresponding to the same time 291B. Likewise in dataset1377C, a plurality of location-specific artificial biometrics of thethen-current depiction 1025 (nominally taken at time 291C pursuant toexecution block 705, e.g.) is within the selected range 277, suggestingthat said biometrics (and the “third” positions to which they pertain)are “more marginal” and deserving of higher prioritization (ranking orconditionally urgent treatment, e.g.) than some or all of the other(over-limit or under-limit) biometrics in dataset 1377C. Many datasets1377 described herein warrant special handling of within-rangelocation-specific biometric values 1473 as contrasted with that ofcorresponding under-limit values 1471 and over-limit values 1472.

In light of teachings herein, numerous existing techniques may beapplied for configuring special-purpose circuitry or other structureseffective for obtaining and applying limits to biometric values asdescribed herein without undue experimentation. See, e.g., U.S. Pat. No.9,420,737 (“Three-dimensional elevation modeling for use in operatingagricultural vehicles”); U.S. Pat. No. 9,378,554 (“Real-time range mapgeneration”); U.S. Pat. No. 9,373,149 (“Autonomous neighborhood vehiclecommerce network and community”); U.S. Pat. No. 9,354,235 (“System andprocess for quantifying potentially mineralizable nitrogen foragricultural crop production”); U.S. Pat. No. 9,340,797 (“Compositionsand methods for control of insect infestations in plants”); U.S. Pat.No. 9,310,354 (“Methods of predicting crop yield using metabolicprofiling”); U.S. Pat. No. 9,412,140 (“Method and system for inspectionof travelers”); U.S. Pat. No. 9,378,065 (“Purposeful computing”); U.S.Pat. No. 8,682,888 (“System and methods for tasking, collecting, anddispatching information reports”); U.S. Pat. No. 9,423,249 (“Biometricmeasurement systems and methods”); U.S. Pat. No. 9,286,511 (“Eventregistration and management system and method employing geo-tagging andbiometrics”); U.S. Pat. No. 9,268,915 (“Systems and methods fordiagnosis or treatment”); U.S. Pat. No. 9,137,246 (“Systems, methods andapparatus for multivariate authentication”); and U.S. Pat. No. 9,014,516(“Object information derived from object images”). These documents areincorporated herein by reference to the extent not inconsistentherewith.

In light of teachings herein, numerous existing techniques may beapplied for configuring special-purpose circuitry or other structureseffective for manifesting and implementing priorities and verdicts asdescribed herein without undue experimentation. See, e.g., U.S. Pat. No.9,311,605 (“Modeling of time-variant grain moisture content fordetermination of preferred temporal harvest windows and estimation ofincome loss from harvesting an overly-dry crop”); U.S. Pat. No.9,390,331 (“System and method for assessing riparian habitats”); U.S.Pat. No. 9,383,750 (“System for predictively managing communicationattributes of unmanned vehicles”); U.S. Pat. No. 9,378,509 (“Methods,apparatus, and articles of manufacture to measure geographical featuresusing an image of a geographical location”); U.S. Pat. No. 9,373,051(“Statistical approach to identifying and tracking targets withincaptured image data”); U.S. Pat. No. 9,355,154 (“Media sequencing methodto provide location-relevant entertainment”); U.S. Pat. No. 9,336,492(“Modeling of re-moistening of stored grain crop for acceptabletime-of-sale moisture level and opportunity windows for operation ofstorage bin fans based on expected atmospheric conditions”); U.S. Pat.No. 9,277,525 (“Wireless location using location estimators”); U.S. Pat.No. 9,269,022 (“Methods for object recognition and relatedarrangements”); U.S. Pat. No. 9,237,416 (“Interactive advisory systemfor prioritizing content”); U.S. Pat. No. 9,202,252 (“System and methodfor conserving water and optimizing land and water use”); U.S. Pat. No.9,131,644 (“Continual crop development profiling using dynamicalextended range weather forecasting with routine remotely-sensedvalidation imagery”); U.S. Pat. No. 9,113,590 (“Methods, apparatus, andsystems for determining in-season crop status in an agricultural cropand alerting users”); U.S. Pat. No. 8,775,428 (“Method and apparatus forpredicting object properties and events using similarity-basedinformation retrieval and modeling”); U.S. Pat. No. 8,146,539 (“Methodof reducing herbaceous fuels in areas susceptible to wildfires”); U.S.Pat. No. 7,764,231 (“Wireless location using multiple mobile stationlocation techniques”); and U.S. Pub. No. 2016/0073573 (“Methods andsystems for managing agricultural activities”). These documents areincorporated herein by reference to the extent not inconsistentherewith.

With respect to the numbered clauses and claims expressed below, thoseskilled in the art will appreciate that recited operations therein maygenerally be performed in any order. Also, although various operationalflows are presented in a sequence(s), it should be understood that thevarious operations may be performed in other orders than those which areillustrated, or may be performed concurrently. Examples of suchalternate orderings may include overlapping, interleaved, interrupted,reordered, incremental, preparatory, supplemental, simultaneous,reverse, or other variant orderings, unless context dictates otherwise.Furthermore, terms like “responsive to,” “related to,” or otherpast-tense adjectives are generally not intended to exclude suchvariants, unless context dictates otherwise. Also in the numberedclauses below, specific combinations of aspects and embodiments arearticulated in a shorthand form such that (1) according to respectiveembodiments, for each instance in which a “component” or other suchidentifiers appear to be introduced (with “a” or “an,” e.g.) more thanonce in a given chain of clauses, such designations may either identifythe same entity or distinct entities; and (2) what might be called“dependent” clauses below may or may not incorporate, in respectiveembodiments, the features of “independent” clauses to which they referor other features described above.

CLAUSES

1. (Independent) A time-sensitive forestry information management systemcomprising:

transistor-based circuitry (as a component of special-purpose circuitry522, 622, e.g.) configured to obtain a current depiction 1025 (at least)of a land tract 250 that includes (at least) aerial photographic data1389 (at least) from one or more aircraft 130, wherein a firstlocation-specific artificial biometric 1102 of said depiction 1025 isassociated with a first position 255 of said land tract, wherein asecond location-specific artificial biometric of said depiction isassociated with a second position 255 of said land tract, and wherein athird location-specific artificial biometric of said depiction isassociated with a third position 255 of said land tract; and

transistor-based circuitry (as a component of special-purpose circuitry522, 622, e.g.) configured to receive a verdict 875 concerning (atleast) said third position of said land tract (at least) from a firstparty 898A who has received an automatic prioritization 1151 of saidthird position over (at least) said first and second positions partlybased on (at least) a current scalar value 1384 of said thirdlocation-specific artificial biometric of said depiction being within arange 277, partly based on a current scalar value of said firstlocation-specific artificial biometric of said depiction being belowsaid range, and partly based on a current scalar value of said secondlocation-specific artificial biometric of said depiction being abovesaid range, wherein (said scalar values and said depiction are “current”insofar that) all of said scalar values of said location-specificartificial biometrics resulted from the one or more aircraft havingreceived (at least some) optical energy 1108 while airborne at a time T1(time 291, e.g.) less than six months before a time T2 (time 292, e.g.)of the current depiction (for the aerial photographic data) and alsoless than six months before a time T3 (time 293, e.g.) of said verdict(being received).

2. The system of any of the above SYSTEM CLAUSES, further comprising:

a motorized drone (drone 1131, e.g.) supporting said transistor-basedcircuitry configured to obtain said current depiction of said land tractthat includes aerial photographic data from one or more aircraft,wherein said first location-specific artificial biometric of saiddepiction is associated with said first position of said land tract,wherein said second location-specific artificial biometric of saiddepiction is associated with said second position of said land tract,and wherein said third location-specific artificial biometric of saiddepiction is associated with said third position of said land tract andsaid transistor-based circuitry configured to receive said verdictconcerning said third position of said land tract from said first partywho has received said automatic prioritization of said third positionover said first and second positions partly based on said current scalarvalue of said third location-specific artificial biometric of saiddepiction being within said range, partly based on said current scalarvalue of said first location-specific artificial biometric of saiddepiction being below said range, and partly based on said currentscalar value of said second location-specific artificial biometric ofsaid depiction being above said range, wherein all of said scalar valuesof said location-specific artificial biometrics resulted from the one ormore aircraft having received optical energy while airborne at said timeT1 less than six months before said time T2 of the current depiction andalso less than six months before said time T3 of said verdict.

3. The system of any of the above SYSTEM CLAUSES, further comprising: amotor vehicle (vessel 230, e.g.) supporting said transistor-basedcircuitry configured to obtain said current depiction of said land tractthat includes aerial photographic data from one or more aircraft,wherein said first location-specific artificial biometric of saiddepiction is associated with said first position of said land tract,wherein said second location-specific artificial biometric of saiddepiction is associated with said second position of said land tract,and wherein said third location-specific artificial biometric of saiddepiction is associated with said third position of said land tract andsaid transistor-based circuitry configured to receive said verdictconcerning said third position of said land tract from said first partywho has received said automatic prioritization of said third positionover said first and second positions partly based on said current scalarvalue of said third location-specific artificial biometric of saiddepiction being within said range, partly based on said current scalarvalue of said first location-specific artificial biometric of saiddepiction being below said range, and partly based on said currentscalar value of said second location-specific artificial biometric ofsaid depiction being above said range, wherein all of said scalar valuesof said location-specific artificial biometrics resulted from the one ormore aircraft having received optical energy while airborne at said timeT1 less than six months before said time T2 of the current depiction andalso less than six months before said time T3 of said verdict.

4. The system of any of the above SYSTEM CLAUSES, wherein the system isconfigured to perform any of the METHOD CLAUSES set forth herein.

5. (Independent) A time-sensitive forestry information management methodcomprising:

invoking transistor-based circuitry configured to obtain a currentdepiction 1025 of a land tract 250 that includes aerial photographicdata 1389 from one or more aircraft 130, wherein a firstlocation-specific artificial biometric 1102 of said depiction 1025 isassociated with a first position 255 of said land tract, wherein asecond location-specific artificial biometric of said depiction isassociated with a second position 255 of said land tract, and wherein athird location-specific artificial biometric of said depiction isassociated with a third position 255 of said land tract; and

invoking transistor-based circuitry configured to receive a verdict 875concerning said third position of said land tract from a first party whohas received an automatic prioritization 1151 of said third positionover said first and second positions partly based on a current scalarvalue 1384 of said third location-specific artificial biometric of saiddepiction being within a range 277, partly based on a current scalarvalue of said first location-specific artificial biometric of saiddepiction being below said range, and partly based on a current scalarvalue of said second location-specific artificial biometric of saiddepiction being above said range, wherein (said scalar values and saiddepiction are “current” insofar that) all of said scalar values of saidlocation-specific artificial biometrics resulted from the one or moreaircraft having received (at least some) optical energy 1108 whileairborne at a time T1 (time 291, e.g.) less than six months before atime T2 (time 292, e.g.) of the current depiction (for the aerialphotographic data) and also less than six months before a time T3 (time293, e.g.) of said verdict (being received).

6. The method of any of the above METHOD CLAUSES, wherein the methodincludes all of the operations depicted in FIG. 7.

7. The method of any of the above METHOD CLAUSES, further comprising:

computing several distance estimates 1383 each as a corresponding one ofsaid current scalar values of said first, second, and thirdlocation-specific artificial biometrics.

8. The method of any of the above METHOD CLAUSES, further comprising:obtaining said range by allowing said first party to select said rangefrom a menu and to define one or more conditions under which the firstparty is to be notified of said prioritization;

determining that the one or more conditions under which the first partyis to be notified of said prioritization are met; and

providing a conditional notification 1351 to the first party of saidprioritization as an automatic and conditional response to the one ormore conditions under which the first party is to be notified of saidprioritization having been met.

9. The method of any of the above METHOD CLAUSES, further comprising:

configuring one or more sensors aboard the one or more aircraft toobtain other aerial photographic data by detecting other optical energyat least 24 hours at a prior time T0 before time T1 from said landtract;

configuring said one or more sensors aboard the one or more aircraft toobtain said aerial photographic data by detecting said optical energy atsaid time T1 from said land tract; and

obtaining said first, second, and third location-specific artificialbiometrics of said depiction as a component of the current depiction atleast by comparing said photographic data from said time T1 against theother photographic data from said prior time T0.

10. The method of any of the above METHOD CLAUSES, further comprising:

configuring one or more sensors aboard the one or more aircraft toobtain said aerial photographic data by detecting said optical energy ator before said time T1 from said land tract.

11. The method of any of the above METHOD CLAUSES, further comprising:

configuring one or more sensors aboard the one or more aircraft toobtain said aerial photographic data by detecting said optical energy ator before said time T1 from said land tract; and

using at least some additional aerial photographic data taken after saidtime T1 and before said time T2 of the current depiction in configuringthe current depiction.

12. The method of any of the above METHOD CLAUSES, further comprising:

configuring one or more sensors aboard the one or more aircraft toobtain said aerial photographic data by detecting said optical energy ator before said time T1 from said land tract; and

including at least some additional aerial photographic data taken aftersaid time T1 and before said time T2 of the current depiction in thecurrent depiction.

13. The method of any of the above METHOD CLAUSES, further comprising:

determining that said current scalar value of said firstlocation-specific artificial biometric of said depiction is below saidrange;

determining that said current scalar value of said secondlocation-specific artificial biometric of said depiction is above saidrange; and

determining that said current scalar value of said thirdlocation-specific artificial biometric of said depiction is within saidrange.

14. The method of any of the above METHOD CLAUSES, further comprising:

receiving at least a component of said range from said first partybefore the current depiction of said land tract is obtained and beforesaid first party receives said automatic prioritization of said thirdposition over said first and second positions.

15. The method of any of the above METHOD CLAUSES, further comprising:

receiving at least a component of said range from a second party 898Bbefore the current depiction of said land tract is obtained and beforesaid first party receives said automatic prioritization of said thirdposition over said first and second positions.

16. The method of any of the above METHOD CLAUSES, further comprising:

allowing a second party to configure one or more sensors aboard the oneor more aircraft and to select and to configure said range (as one menuoption among a plurality of menu options, e.g.) before the currentdepiction of said land tract is obtained and before said first partyreceives said automatic prioritization (as a conditional notification1351, e.g.) of said third position over said first and second positions.

17. The method of any of the above METHOD CLAUSES, further comprising:obtaining a positive decision 901 concerning one or more drone routes923 that selectively include said third position (to distribute Douglasfir seeds selectively to a target planting region that includes saidthird position, e.g.) as a component of said verdict (excluding eitherthe first or second region, e.g.).

18. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a negative planting decision 902 (not to plant said thirdposition, e.g.) as a component of said verdict.

19. The method of any of the above METHOD CLAUSES, further comprising:

obtaining an organic species identification 903 as a component of saidverdict.

20. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a payload module identifier 921 (a serial number identifying asensor-containing or payload item to be carried by an aircraft, e.g.) asa component of said verdict.

21. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a drone-executable command sequence 922 (mapping a flight andmaterial deposition pattern executable by a particular drone, e.g.) as acomponent of said verdict.

22. The method of any of the above METHOD CLAUSES, further comprising:

obtaining an herbicide identification 931 as a component of saidverdict.

23. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a pesticide identification 932 as a component of said verdict.

24. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a therapeutic bioactive material identification 935 as acomponent of said verdict.

25. The method of any of the above METHOD CLAUSES, further comprising:obtaining a crop species identification 943 (naming “Douglas fir” inlieu of a deciduous crop tree, e.g.) as a component of said verdict.

26. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a dataset 1377B-C having a minimum value as said currentscalar value 1471 of said first location-specific artificial biometricof said depiction 1025, a maximum value as said current scalar value1472 of said second location-specific artificial biometric of saiddepiction, and an intermediate value 1473 as said current scalar valueof said third location-specific artificial biometric of said depiction;and

deriving said range as having a lower limit (limit 261, e.g.) above saidminimum value and below said intermediate value and as having an upperlimit (limit 263, e.g.) above said intermediate value and below saidmaximum value.

27. The method of any of the above METHOD CLAUSES, further comprising:

obtaining a dataset 1377B-C having a minimum value as said currentscalar value 1471 of said first location-specific artificial biometricof said depiction 1025, a maximum value as said current scalar value1472 of said second location-specific artificial biometric of saiddepiction, and an intermediate value 1473 as said current scalar valueof said third location-specific artificial biometric of said depiction;and

deriving said range as having a lower limit (limit 261, e.g.) halfwaybetween said minimum value and said intermediate value and as having anupper limit (limit 263, e.g.) halfway between said intermediate valueand said maximum value.

28. The method of any of the above METHOD CLAUSES, wherein saiddepiction 1025 includes said automatic prioritization 1151 and whereinsaid automatic prioritization 1151 ranks said third position above saidfirst and second positions as a conditional response to said thirdlocation-specific artificial biometric of said depiction being withinsaid range and to said first and second location-specific artificialbiometrics of said depiction being outside said range.

29. The method of any of the above METHOD CLAUSES, wherein saidprioritization 1151 manifests a conditional notification 1351 sent inresponse to said third location-specific artificial biometric of saiddepiction being within said range and to said first and secondlocation-specific artificial biometrics of said depiction being outsidesaid range.

30. The method of any of the above METHOD CLAUSES, wherein a serverreceives said verdict at time T3 within a month of both said time T1 atwhich said optical energy was detected and said time T2 at which saidcurrent depiction was generated.

31. The method of any of the above METHOD CLAUSES, wherein a serverreceives said verdict at time T3 within a week of both said time T1 atwhich said optical energy was detected and said time T2 at which saidcurrent depiction was generated.

32. The method of any of the above METHOD CLAUSES, wherein a serverreceives said verdict at time T3 within 24 hours of both said time T1 atwhich said optical energy was detected and said time T2 at which saidcurrent depiction was generated.

33. The method of any of the above METHOD CLAUSES, wherein a serverreceives said verdict at time T3 within 3 hours of both said time T1 atwhich said optical energy was detected and said time T2 at which saidcurrent depiction was generated.

34. The method of any of the above METHOD CLAUSES, wherein saidobtaining said depiction of said land tract that includes aerialphotographic data from one or more aircraft comprises:

selectively including in said depiction an aerial photograph 1387 of atleast a part of said land tract that overlaps said third position whileselectively omitting from said depiction at least a portion of saidphotographic data that depicts the first or second positions of saidland tract as a component of automatically prioritizing said thirdposition over said first and second positions partly based on saidcurrent scalar value of said third location-specific artificialbiometric of said depiction being within said range, partly based onsaid current scalar value of said first location-specific artificialbiometric of said depiction being below said range, and partly based onsaid current scalar value of said second location-specific artificialbiometric of said depiction being above said range.

35. The method of any of the above METHOD CLAUSES, wherein saidobtaining said depiction of said land tract that includes aerialphotographic data from one or more aircraft comprises:

selectively including in said depiction 1025 an aerial photograph 1387of at least a part of said land tract 250 that overlaps said thirdposition 255 while selectively omitting from said depiction at least aportion of said photographic data that depicts the first or secondpositions of said land tract.

36. The method of any of the above METHOD CLAUSES, wherein saidreceiving said verdict 875 concerning said third position of said landtract from said first party who has received said automaticprioritization of said third position over said first and secondpositions partly based on said current scalar value of said thirdlocation-specific artificial biometric of said depiction being within arange, partly based on said current scalar value of said firstlocation-specific artificial biometric of said depiction being belowsaid range, and partly based on said current scalar value of said secondlocation-specific artificial biometric of said depiction being abovesaid range comprises:

selectively including in said depiction an aerial photograph 1387 of atleast a part of said land tract that overlaps said third position whileselectively omitting from said depiction at least a portion of saidphotographic data that depicts the first or second positions of saidland tract as a component of automatically prioritizing said thirdposition over said first and second positions partly based on saidcurrent scalar value of said third location-specific artificialbiometric of said depiction being within said range, partly based onsaid current scalar value of said first location-specific artificialbiometric of said depiction being below said range, and partly based onsaid current scalar value of said second location-specific artificialbiometric of said depiction being above said range.

37. The method of any of the above METHOD CLAUSES, further comprising:

acting upon said verdict (by initiating a planting, materialdistribution, or supplemental surveillance task, e.g.).

While various system, method, article of manufacture, or otherembodiments or aspects have been disclosed above, also, othercombinations of embodiments or aspects will be apparent to those skilledin the art in view of the above disclosure. The various embodiments andaspects disclosed above are for purposes of illustration and are notintended to be limiting, with the true scope and spirit being indicatedin the final claim set that follows.

What is claimed is:
 1. A time-sensitive forestry information managementmethod comprising: invoking transistor-based circuitry configured toconfigure one or more sensors aboard one or more airborne vehicles toobtain photographic data in memory thereof by detecting at least someoptical energy at a first time T1 from a land tract; invokingtransistor-based circuitry configured to obtain a depiction of said landtract that includes said photographic data from the one or more airbornevehicles at a second time T2, wherein a first location-specificartificial biometric of said depiction is associated with a firstposition of said land tract, wherein a second location-specificartificial biometric of said depiction is associated with a secondposition of said land tract, and wherein a third location-specificartificial biometric of said depiction is associated with a thirdposition of said land tract; invoking transistor-based circuitryconfigured to determine that a scalar value of said firstlocation-specific artificial biometric of said depiction is below arange; invoking transistor-based circuitry configured to determine thata scalar value of said second location-specific artificial biometric ofsaid depiction is above said range; invoking transistor-based circuitryconfigured to determine that a scalar value of said thirdlocation-specific artificial biometric of said depiction is within saidrange; invoking transistor-based circuitry configured automatically togenerate an automatic prioritization of said third position of said landtract over said first and second positions of said land tract partlybased on said scalar value of said third location-specific artificialbiometric of said depiction being within a range, partly based on saidscalar value of said first location-specific artificial biometric ofsaid depiction being below said range, and partly based on said scalarvalue of said second location-specific artificial biometric of saiddepiction being above said range; invoking transistor-based circuitryconfigured automatically to transmit said prioritization of said thirdlocation-specific artificial biometric of said depiction over said firstand second location-specific artificial biometrics of said depictionpartly based on said scalar value of said third location-specificartificial biometric of said depiction being within a range, partlybased on said scalar value of said first location-specific artificialbiometric of said depiction being below said range, and partly based onsaid scalar value of said second location-specific artificial biometricof said depiction being above said range, wherein said first time T1 atwhich said optical energy from said land tract was detected and saidsecond time T2 at which said depiction of said land tract that includessaid photographic data was obtained were both within 6 months beforesaid third time at which said verdict concerning said third position ofsaid land tract was received; invoking transistor-based circuitryconfigured to receive a verdict concerning said third position of saidland tract at a third time T3 from a party who has received saidprioritization of said third location-specific artificial biometric ofsaid depiction over said first and second location-specific artificialbiometrics of said depiction partly based on a scalar value of saidthird location-specific artificial biometric of said depiction beingwithin a range, partly based on a scalar value of said firstlocation-specific artificial biometric of said depiction being belowsaid range, and partly based on a scalar value of said secondlocation-specific artificial biometric of said depiction being abovesaid range, wherein said first time T1 at which said optical energy fromsaid land tract was detected and said second time T2 at which saiddepiction of said land tract that includes said photographic data wasobtained were both within 6 months before said third time T3 ofreceiving said verdict concerning said third position of said landtract; and invoking transistor-based circuitry configured to act uponsaid verdict.
 2. The time-sensitive forestry information managementmethod of claim 1, wherein said first, second, and thirdlocation-specific artificial biometrics indicate at least one of agrowth indicator, a foliage height, a health indicator, or a mortality.3. The time-sensitive forestry information management method of claim 1,wherein said invoking transistor-based circuitry configured to obtainsaid depiction of said land tract that includes said photographic datafrom the one or more airborne vehicles comprises: invokingtransistor-based circuitry configured to include selectively in saiddepiction a photograph of at least a part of said land tract thatoverlaps said third position while selectively omitting from saiddepiction at least a portion of said photographic data that depicts thefirst or second positions of said land tract.
 4. The time-sensitiveforestry information management method of claim 1, wherein saidprioritization manifests a conditional notification sent in response tosaid third location-specific artificial biometric of said depictionbeing within said range and to said first and second location-specificartificial biometrics of said depiction being outside said range.
 5. Thetime-sensitive forestry information management method of claim 1,wherein said depiction includes said prioritization and wherein saidprioritization ranks said third position above said first and secondpositions as a conditional response to said third location-specificartificial biometric of said depiction being within said range and tosaid first and second location-specific artificial biometrics of saiddepiction being outside said range.
 6. A time-sensitive forestryinformation management method comprising: invoking transistor-basedcircuitry configured to obtain a current depiction of a land tract thatincludes aerial photographic data from one or more aircraft, wherein afirst location-specific artificial biometric of said depiction isassociated with a first position of said land tract, wherein a secondlocation-specific artificial biometric of said depiction is associatedwith a second position of said land tract, and wherein a thirdlocation-specific artificial biometric of said depiction is associatedwith a third position of said land tract; and invoking transistor-basedcircuitry configured to receive a verdict concerning said third positionof said land tract from a first party who has received an automaticprioritization of said third position over said first and secondpositions partly based on a current scalar value of said thirdlocation-specific artificial biometric of said depiction being within arange, partly based on a current scalar value of said firstlocation-specific artificial biometric of said depiction being belowsaid range, and partly based on a current scalar value of said secondlocation-specific artificial biometric of said depiction being abovesaid range, wherein all of said scalar values of said location-specificartificial biometrics resulted from the one or more aircraft havingreceived optical energy while airborne at a time T1 less than six monthsbefore a time T2 of the current depiction and also less than six monthsbefore a time T3 of said verdict.
 7. The time-sensitive forestryinformation management method of claim 6, further comprising: invokingtransistor-based circuitry configured to compute several distanceestimates each as a corresponding one of said current scalar values ofsaid first, second, and third location-specific artificial biometrics.8. The time-sensitive forestry information management method of claim 6,further comprising: invoking transistor-based circuitry configured toconfigure one or more sensors aboard the one or more aircraft to obtainsaid aerial photographic data by detecting said optical energy at orbefore said time T1 from said land tract; invoking transistor-basedcircuitry configured to use at least some additional aerial photographicdata taken after said time T1 and before said time T2 of the currentdepiction in configuring the current depiction; invokingtransistor-based circuitry configured to configure one or more sensorsaboard the one or more aircraft to obtain other aerial photographic databy detecting other optical energy at least 24 hours at a prior time T0before time T1 from said land tract; invoking transistor-based circuitryconfigured to configure said one or more sensors aboard the one or moreaircraft to obtain said aerial photographic data by detecting saidoptical energy at said time T1 from said land tract; and invokingtransistor-based circuitry configured to obtain said first, second, andthird location-specific artificial biometrics of said depiction as acomponent of the current depiction at least by comparing saidphotographic data from said time T1 against the other photographic datafrom said prior time T0.
 9. The time-sensitive forestry informationmanagement method of claim 6, further comprising: invokingtransistor-based circuitry configured to determine that said currentscalar value of said first location-specific artificial biometric ofsaid depiction is below said range; invoking transistor-based circuitryconfigured to determine that said current scalar value of said secondlocation-specific artificial biometric of said depiction is above saidrange; and invoking transistor-based circuitry configured to determinethat said current scalar value of said third location-specificartificial biometric of said depiction is within said range.
 10. Thetime-sensitive forestry information management method of claim 6,further comprising: invoking transistor-based circuitry configured toreceive at least a component of said range before the current depictionof said land tract is obtained and before said first party receives saidautomatic prioritization of said third position over said first andsecond positions.
 11. The time-sensitive forestry information managementmethod of claim 6, further comprising: invoking transistor-basedcircuitry configured to allow a second party to configure one or moresensors aboard the one or more aircraft and to select and to configuresaid range before the current depiction of said land tract is obtainedand before said first party receives said automatic prioritization ofsaid third position over said first and second positions.
 12. Thetime-sensitive forestry information management method of claim 6,further comprising: invoking transistor-based circuitry configured toobtain a positive decision concerning one or more drone routes or anorganic species identification or a payload module identifier as acomponent of said verdict.
 13. The time-sensitive forestry informationmanagement method of claim 6, further comprising: invokingtransistor-based circuitry configured to obtain a drone-executablecommand sequence as a first component of said verdict; and invokingtransistor-based circuitry configured to obtain at least one of anherbicide identification or a pesticide identification as a secondcomponent of said verdict.
 14. The time-sensitive forestry informationmanagement method of claim 6, wherein said first, second, and thirdpositions are first, second, and third microsites, further comprising:invoking transistor-based circuitry configured to extend said thirdposition to include a succession of additional adjacent micrositespartly based on the value of the biometric of each microsite in thesuccession being within said range and partly based on each microsite ofthe succession being adjacent another microsite of the succession. 15.The time-sensitive forestry information management method of claim 6,wherein said prioritization manifests a conditional notification sent inresponse to said third location-specific artificial biometric of saiddepiction being within said range and to said first and secondlocation-specific artificial biometrics of said depiction being outsidesaid range.
 16. The time-sensitive forestry information managementmethod of claim 6, wherein a server receives said verdict at time T3within 3 hours of both said time T1 at which said optical energy wasdetected and said time T2 at which said current depiction was generated.17. The time-sensitive forestry information management method of claim6, wherein said invoking transistor-based circuitry configured to obtainsaid depiction of said land tract that includes aerial photographic datafrom one or more aircraft comprises: invoking transistor-based circuitryconfigured to include selectively in said depiction an aerial photographof at least a part of said land tract that overlaps said third positionwhile selectively omitting from said depiction at least a portion ofsaid photographic data that depicts the first or second positions ofsaid land tract as a component of automatically prioritizing said thirdposition over said first and second positions partly based on saidcurrent scalar value of said third location-specific artificialbiometric of said depiction being within said range, partly based onsaid current scalar value of said first location-specific artificialbiometric of said depiction being below said range, and partly based onsaid current scalar value of said second location-specific artificialbiometric of said depiction being above said range.
 18. Thetime-sensitive forestry information management method of claim 6,wherein said invoking transistor-based circuitry configured to obtainsaid depiction of said land tract that includes aerial photographic datafrom one or more aircraft comprises: invoking transistor-based circuitryconfigured to include selectively in said depiction an aerial photographof at least a part of said land tract that overlaps said third positionwhile selectively omitting from said depiction at least a portion ofsaid photographic data that depicts the first or second positions ofsaid land tract.
 19. The time-sensitive forestry information managementmethod of claim 6, wherein said invoking transistor-based circuitryconfigured to receive said verdict concerning said third position ofsaid land tract from said first party who has received said automaticprioritization of said third position over said first and secondpositions partly based on said current scalar value of said thirdlocation-specific artificial biometric of said depiction being within arange, partly based on said current scalar value of said firstlocation-specific artificial biometric of said depiction being belowsaid range, and partly based on said current scalar value of said secondlocation-specific artificial biometric of said depiction being abovesaid range comprises: invoking transistor-based circuitry configured toinclude selectively in said depiction an aerial photograph of at least apart of said land tract that overlaps said third position whileselectively omitting from said depiction at least a portion of saidphotographic data that depicts the first or second positions of saidland tract as a component of automatically prioritizing said thirdposition over said first and second positions partly based on saidcurrent scalar value of said third location-specific artificialbiometric of said depiction being within said range, partly based onsaid current scalar value of said first location-specific artificialbiometric of said depiction being below said range, and partly based onsaid current scalar value of said second location-specific artificialbiometric of said depiction being above said range.
 20. A time-sensitiveforestry information management system comprising: transistor-basedcircuitry configured to obtain a current depiction of a land tract thatincludes aerial photographic data from one or more aircraft, wherein afirst location-specific artificial biometric of said depiction isassociated with a first position of said land tract, wherein a secondlocation-specific artificial biometric of said depiction is associatedwith a second position of said land tract, and wherein a thirdlocation-specific artificial biometric of said depiction is associatedwith a third position of said land tract; and transistor-based circuitryconfigured to receive a verdict concerning said third position of saidland tract from a first party who has received an automaticprioritization of said third position over said first and secondpositions partly based on a current scalar value of said thirdlocation-specific artificial biometric of said depiction being within arange, partly based on a current scalar value of said firstlocation-specific artificial biometric of said depiction being belowsaid range, and partly based on a current scalar value of said secondlocation-specific artificial biometric of said depiction being abovesaid range, wherein all of said scalar values of said location-specificartificial biometrics resulted from the one or more aircraft havingreceived optical energy while airborne at a time T1 less than six monthsbefore a time T2 of the current depiction and also less than six monthsbefore a time T3 of said verdict.